The latest blog posts to take off on Hacker News. 6,335 posts.
Learning and motivation are driven by internal and external rewards. Many of our day-to-day behaviours are guided by predicting, or anticipating, whether a given action will result in a positive (that is, rewarding) outcome. The study of how organisms learn from experience to correctly anticipate rewards has been a…
We are releasing HiPlot, a lightweight interactive visualization tool to help AI researchers discover correlations and patterns in high-dimensional data.
Facebook AI has developed a new technique to mark the images in a dataset, so that researchers can then determine if a particular machine learning model...
I originally wrote this guide in back in December 2017 for the OpenAI Fellows program
We are standardizing OpenAI’s deep learning framework on PyTorch.
Posted by Daniel Adiwardana, Senior Research Engineer, and Thang Luong, Senior Research Scientist, Google Research, Brain Team Modern conversatio...
In this article, I cover the theory behind receipt digitization and implement an end-to-end pipeline using OpenCV and Tesseract. I also review a few important papers that do Receipt Digitization using Deep Learning.
This is the second part of the roadmap of IntelliJ IDEA and IntelliJ-based IDEs for 2020. The first part of the roadmap was focused mostly on low-level features in the platform. In this post we’ll be
Extract table from image with Nanonets table detection OCR. Learn OCR table Deep Learning methods to detect tables in images or PDF documents.
Posted by Nikita Kitaev, Student Researcher, UC Berkeley and Łukasz Kaiser, Research Scientist, Google Research Understanding sequential data — s...
In our study published in Nature, we demonstrate how artificial intelligence research can drive and accelerate new scientific discoveries. We’ve built a dedicated, interdisciplinary team in hopes of using AI to push basic research forward: bringing together experts from the fields of structural biology, physics, and…
by Carles Gelada and Jacob Buckman WARNING: This is an old version of this blogpost, and if you are a Bayesian, it might make you angry. Click here for an updated post with the same content. Context: About a month ago Carles asserted on Twitter that Bayesian Neural Networks make...
the real reason zsh beats bash • how I got twice as fast in python • autocompleting all the things • maximizing user-interface bandwidth
Facebook AI has developed the first neural network that uses symbolic reasoning to solve advanced mathematics problems.
We have open-sourced wav2letter@anywhere, an inference framework for online speech recognition that delivers state-of-the-art performance.
The Case for Bayesian Deep Learning Andrew Gordon Wilson Abstract Bayesian inference is especially compelling for deep neural networks. The key distinguishing property of a Bayesian approach is margin
Posted by Radu Soricut and Zhenzhong Lan, Research Scientists, Google Research Ever since the advent of BERT a year ago, natural language research...
Today Lyft is excited to announce the open sourcing of Flyte, a structured programming and distributed processing platform for highly…
Almost 25 years after Kasparov vs. Deep Blue, another seminal man vs. machine matchup: Neither competitor has much to be proud of here. White has a poor opening. Black screws up and loses his queen…
MIT researchers have developed an automated machine-learning model that uses probability techniques to significantly outperform human Wall Street analysts in predicting quarterly business sales.
Estimating expected time of arrival (ETA) is crucial to what we do at Lyft. Estimates go directly to riders and drivers using our apps, as…
Dive deep into OCR with Tesseract, including Pytesseract integration, training with custom data, limitations, and comparisons with enterprise solutions.
